This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This second volume, Inference, builds on the foundational topics established in volume I to introduce students to techniques for inferring unknown variables and quantities, including Bayesian inference, Monte Carlo Markov Chain methods, maximum-likelihood estimation, hidden Markov models, Bayesian networks, and…
This is the second volume of a three volume textbook. We encourage instructors to refer to the Course Guide in the Resources area for more information on how the volumes can be combined or used individually to support different courses.
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Foundations, Volume 1
Online publication date: 17 February 2023
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Learning, Volume 3
Online publication date: 24 February 2023
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Online publication date: 02 February 2023
Online publication date: 05 August 2015